ArticleBMC pregnancy and childbirth2020
Nomogram for prediction of gestational diabetes mellitus in urban, Chinese, pregnant women.
Article in BMC pregnancy and childbirth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.
- Maternal metabolic factors and the association with gestational diabetes: A systematic review and meta-analysis.Diabetes/metabolism research and reviews · 2022Pooled it
- Risk factors associated with gestational diabetes mellitus in Ghana: a prospective cohort study.Scientific reports · 2026Article
- Screening and Prognostic Performance of Pre-Pregnancy BMI for Predicting Gestational Diabetes Mellitus in Asian Populations: A Systematic Review and Meta-Analysis.Nursing reports (Pavia, Italy) · 2026Review
- LASSO regression-derived first-trimester (9-14Archives of gynecology and obstetrics · 2026Article
- Early-pregnancy trunk phase angle derived from bioelectrical impedance analysis for the prediction of gestational diabetes mellitus.Frontiers in endocrinology · 2026Article
- Early prediction of late-pregnancy hypertriglyceridemia in women with gestational diabetes: development and internal validation of a clinical risk model.Frontiers in endocrinology · 2026Article
- Novel definition of time range and risk factors of pregnant women with gestational diabetes mellitus detected early in pregnancy a cluster analysis using clinical data of the German GestDiab cohort.Diabetology & metabolic syndrome · 2025Article
- Development and multicenter validation of a novel model for selective screening of gestational diabetes mellitus: the Vietnam gestational diabetes mellitus study.BMC pregnancy and childbirth · 2025Article
- Prediction of Gestational Diabetes Mellitus: A Nomogram Model Incorporating Lifestyle, Nutrition and Health Literacy Factors.Nutrients · 2025Article
- Review
- First trimester hepatic steatosis index as a predictor of gestational diabetes mellitus: a cohort study in Northwestern China.Scientific reports · 2025Article
- Development and validation of a prediction model for gestational diabetes mellitus risk among women from 8 to 14 weeks of gestation in Western China.BMC pregnancy and childbirth · 2025Article
- Risk Factors for Gestational Diabetes Mellitus in Mainland China: A Systematic Review and Meta-Analysis.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Review
- Identifying Predictor Variables for a Composite Risk Prediction Tool for Gestational Diabetes and Hypertensive Disorders of Pregnancy: A Modified Delphi Study.Healthcare (Basel, Switzerland) · 2024Article
- A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Pregnant Chinese Women.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2023Article
- Prevalence of abnormal glucose values and gestational diabetes mellitus among pregnant women in Xi'an from 2015 to 2021.BMC pregnancy and childbirth · 2023Article
- Development of machine learning models to predict gestational diabetes risk in the first half of pregnancy.BMC pregnancy and childbirth · 2023Article
- Predicting the Risk of Insulin-Requiring Gestational Diabetes before Pregnancy: A Model Generated from a Nationwide Population-Based Cohort Study in Korea.Endocrinology and metabolism (Seoul, Korea) · 2023Article
- Predictive value of first-trimester GPR120 levels in gestational diabetes mellitus.Frontiers in endocrinology · 2023Article
- Multi-omics and machine learning for the prevention and management of female reproductive health.Frontiers in endocrinology · 2023Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundThis study sought to develop and validate a nomogram for prediction of gestational diabetes mellitus (GDM) in an urban, Chinese, antenatal population.
methodsAge, pre-pregnancy body mass index (BMI), fasting plasma glucose (FPG) in the first trimester and diabetes in first degree relatives were incorporated as validated risk factors. A prediction model (nomogram) for GDM was developed using multiple logistic regression analysis, from a retrospective study conducted on 3956 women who underwent their first antenatal visit during 2015 in Shanghai. Performance of the nomogram was assessed through discrimination and calibration. We refined the predicting model with t-distributed stochastic neighbor embedding (t-SNE) to distinguish GDM from non-GDM. The results were validated using bootstrap resampling and a prospective cohort of 6572 women during 2016 at the same institution.
resultsAdvanced age, pre-pregnancy BMI, high first-trimester, fasting, plasma glucose, and, a family history of diabetes were positively correlated with the development of GDM. This model had an area under the receiver operating characteristic (ROC) curve of 0.69 [95% CI:0.67-0.72, p < 0.0001]. The calibration curve for probability of GDM showed good consistency between nomogram prediction and actual observation. In the validation cohort, the ROC curve was 0.70 [95% CI: 0.68-0.72, p < 0.0001] and the calibration plot was well calibrated. In exploratory and validation cohorts, the distinct regions of GDM and non-GDM were distinctly separated in the t-SNE, generating transitional boundaries in the image by color difference. Decision curve analysis showed that the model had a positive net benefit at threshold between 0.05 and 0.78.
conclusionsThis study demonstrates the ability of our model to predict the development of GDM in women, during early stage of pregnancy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.